Test automation for robotic process automation

ABSTRACT

A robotic process automation (RPA) robot performs fuzzing on a workflow. The robot provides a randomized typed data input in a workflow, and executes the workflow as a black box with the randomized typed data input. The robot creates test case when a new path is discovered based on an output of the workflow, and terminates the fuzzing when a desired path coverage has been reached.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation-in-part of, and claims the benefit of, U.S. patent application Ser. No. 16/854,733 filed Apr. 21, 2020. The subject matter of this earlier filed application is hereby incorporated by reference in its entirety.

FIELD

The present invention generally relates to robotic process automation (RPA), and more specifically, to RPA for workflow in production testing.

BACKGROUND

Digital transformation requires businesses to continuously exploit digital technologies to create new sources of customer value and increase operational agility in service of customers. For example, wherever possible, the application of software and automation is implemented to reduce cost and time to market.

Process automation plays a key role in this transformation as it has the potential to substantially increase efficiency, and therefore, create a competitive advantage. For instance, RPA represents a rather new market, being around just for a few years. RPA has profited from a quick adoption by enterprise customers, resulting in the creation of thousands of bots for automating processes.

However, a lot of those bots may stop working for various reasons. For example, the low stability of bots is due to application changes, environment changes and fragile automation itself. Unlike other automation areas, such as test automation that has been around for 20 plus years, RPA did not have to deal with maintenance, and implementations often focused on happy paths rather than resilience and exception handling. While this issue has been partially addressed by applying best practices and tool support for exception handling and debugging, considering a high-level view on automation quality and digital transformation, a platform that addresses maintenance in several areas is needed.

SUMMARY

Certain embodiments of the present invention may provide solutions to the problems and needs in the art that have not yet been fully identified, appreciated, or solved by current RPA technologies. For example, some embodiments of the present invention pertain to creating and executing test cases for existing workflows (or workflows under test) and fuzzing the workflows to create the test cases.

In an embodiment, a computer-implemented method for performing fuzzing on a workflow using a RPA robot includes providing, by the RPA robot, a randomized typed data input in a workflow, and executing, by the RPA robot, the workflow as a black box with the randomized typed data input. The method also includes creating, by the RPA robot, a test case when a new path is discovered based on an output of the workflow, and terminating, by the RPA robot, the method when a desired path coverage has been reached.

In another embodiment, a non-transitory computer-readable medium storing a computer program comprises a RPA robot to perform fuzzing on a workflow. The computer program is configured to cause at least one processor to perform providing a randomized typed data input in a workflow, and executing the workflow as a black box with the randomized typed data input. The computer program is further configured to cause at least one processor to perform creating a test case when a new path is discovered based on an output of the workflow, and terminating the method when a desired path coverage has been reached.

In yet another embodiment, a system using a robotic process automation (RPA) robot for fuzzing a workflow includes memory comprises computer programmable instructions. The computer programmable instructions comprise the RPA robot. The system also includes at least one processor. The computer programmable instructions are configured to cause at least one processor to perform providing a randomized typed data input in a workflow, and executing the workflow as a black box with the randomized typed data input. The computer programmable instructions are further configured to cause at least one processor to perform creating a test case when a new path is discovered based on an output of the workflow, and terminating the method when a desired path coverage has been reached.

BRIEF DESCRIPTION OF THE DRAWINGS

In order that the advantages of certain embodiments of the invention will be readily understood, a more particular description of the invention briefly described above will be rendered by reference to specific embodiments that are illustrated in the appended drawings. While it should be understood that these drawings depict only typical embodiments of the invention and are not therefore to be considered to be limiting of its scope, the invention will be described and explained with additional specificity and detail through the use of the accompanying drawings, in which:

FIG. 1 is an architectural diagram illustrating an RPA system, according to an embodiment of the present invention.

FIG. 2 is an architectural diagram illustrating a deployed RPA system, according to an embodiment of the present invention.

FIG. 3 is an architectural diagram illustrating the relationship between a designer, activities, and drivers, according to an embodiment of the present invention.

FIG. 4 is an architectural diagram illustrating an RPA system, according to an embodiment of the present invention.

FIG. 5 is an architectural diagram illustrating a computing system configured to create and publish one or more test cases, according to an embodiment of the present invention.

FIG. 6 is a flow diagram illustrating a process for creating a test case, according to an embodiment of the present invention.

FIG. 7 is a flow diagram illustrating a process for publishing a test case, according to an embodiment of the present invention.

FIG. 8 is a flow diagram illustrating a process for executing a test case, according to an embodiment of the present invention.

FIG. 9 is a flow diagram illustrating a process for creating a data-driven workflow test case, according to an embodiment of the present invention.

FIG. 10 is a graphical user interface (GUI) illustrating a workflow being selected in Studio™, according to an embodiment of the present invention.

FIG. 11 is a GUI illustrating a ‘given-when-then’ template, according to an embodiment of the present invention.

FIG. 12 is a GUI illustrating a ‘when’ module, according to an embodiment of the present invention.

FIG. 13, which is a GUI illustrating preconditions entered in the ‘given’ module, according to an embodiment of the present invention.

FIGS. 14 and 15 are GUIs illustrating the mocking of the workflow under test, according to an embodiment of the present invention.

FIG. 16 is a GUI illustrating a ‘then’ module, according to an embodiment of the present invention.

FIGS. 17 and 18 are GUIs illustrating an executed workflow, according to an embodiment of the present invention.

FIG. 19 is a GUI illustrating test cases section having a column for ‘Linked Process’, according to an embodiment of the present invention.

FIG. 20 is a GUI illustrating test results from executed workflow test cases, according to an embodiment of the present invention.

FIG. 21 is a GUI illustrating the ‘Process’ section of Orchestrator™, according to an embodiment of the present invention.

FIG. 22 is a GUI illustrating a menu option to open the workflow in Studio™, according to an embodiment of the present invention.

FIG. 23 us a GUI illustrating affected workflow and a test case in Studio™, according to an embodiment of the present invention.

FIG. 24 is a GUI illustrating a table within Excel®, according to an embodiment of the present invention.

FIG. 25 is a illustrating a workflow that is to be selected, according to an embodiment of the present invention.

FIG. 26 is a GUI illustrating a ‘Data-Driven Test Case’ menu allowing a user to select the data source, according to an embodiment of the present invention.

FIG. 27 is a GUI illustrating a menu option allowing fields to be selected, according to an embodiment of the present invention.

FIG. 28 is a GUI illustrating a menu option for allowing a user to select one or more available columns within the selected Excel® sheet, according to an embodiment of the present invention.

FIG. 29 is a GUI illustrating a menu option showing an option to select ‘Import Data Set’, according to an embodiment of the present invention.

FIG. 30 is a GUI illustrating a first test case created from the data set, according to an embodiment of the present invention.

FIG. 31 is a GUI illustrating a test case with multiple test data variations, according to an embodiment of the present invention.

FIG. 32 is a GUI illustrating a menu option to set the one or more test cases to be publishable, according to an embodiment of the present invention.

FIG. 33 a GUI illustrating an application for publishing in Studio®, according to an embodiment of the present invention.

FIG. 34 is a GUI illustrating a deployment process, according to an embodiment of the present invention.

FIG. 35 is a GUI illustrating the created test cases in the ‘Test Case’ section, according to an embodiment of the present invention.

FIG. 36 is a flow diagram illustrating a process for executing a workflow, according to an embodiment of the present invention.

FIG. 37 is a flow diagram illustrating a process for performing symbolic execution, according to an embodiment of the present invention.

FIG. 38 is a flow diagram illustrating a process for performing fuzzing, according to an embodiment of the present invention.

DETAILED DESCRIPTION OF THE EMBODIMENTS

Some embodiments pertain to creating and executing test cases for existing workflows (or workflows under test). For example, some embodiments provide a solution for common functional application testing, i.e., to test an application directly within development. This allows a developer to catch application changes early on, and populate required adaptions for RPA. Some additional embodiments may provide a solution for functional workflow testing, i.e., testing automated workflows within IT-hosted test environments to catch automation issues and environmental changes (e.g., operating system updates, updated to the environment, or Microsoft Windows® updates) before the application is in production, and populate required adaptions for RPA.

It should be appreciated that the need for testing automated workflows has been recognized. There have been several internal and external initiatives that tried to provide solutions for testing automated workflows, such as RE-framework, which provides an infrastructure for Unit Testing, or the UiPath® functional testing of workflows.

Some embodiments provide a solution to the deficiencies of previously initiatives. For example, some embodiments allow for the creation of test cases for existing workflows or parts of the existing workflows. These test cases may be frequently executed to catch environmental and automation issues. When a failing workflow is identified, the RPA developer is notified. In some additional embodiments, data-driven workflow test cases are created so a data set can be injected from an external source. This data set may include Excel®, JSON, DB, to name a few. These embodiments may reduce the manual effort to create automated workflow test cases.

FIG. 1 is an architectural diagram illustrating an RPA system 100, according to an embodiment of the present invention. RPA system 100 includes a designer 110 that allows a developer to design and implement workflows. Designer 110 may provide a solution for application integration, as well as automating third-party applications, administrative Information Technology (IT) tasks, and business IT processes. Designer 110 may facilitate development of an automation project, which is a graphical representation of a business process. Simply put, designer 110 facilitates the development and deployment of workflows and robots.

The automation project enables automation of rule-based processes by giving the developer control of the execution order and the relationship between a custom set of steps developed in a workflow, defined herein as “activities.” One commercial example of an embodiment of designer 110 is UiPath Studio™. Each activity may include an action, such as clicking a button, reading a file, writing to a log panel, etc. In some embodiments, workflows may be nested or embedded.

Some types of workflows may include, but are not limited to, sequences, flowcharts, Finite State Machines (FSMs), and/or global exception handlers. Sequences may be particularly suitable for linear processes, enabling flow from one activity to another without cluttering a workflow. Flowcharts may be particularly suitable to more complex business logic, enabling integration of decisions and connection of activities in a more diverse manner through multiple branching logic operators. FSMs may be particularly suitable for large workflows. FSMs may use a finite number of states in their execution, which are triggered by a condition (i.e., transition) or an activity. Global exception handlers may be particularly suitable for determining workflow behavior when encountering an execution error and for debugging processes.

Once a workflow is developed in designer 110, execution of business processes is orchestrated by conductor 120, which orchestrates one or more robots 130 that execute the workflows developed in designer 110. One commercial example of an embodiment of conductor 120 is UiPath Orchestrator™. Conductor 120 facilitates management of the creation, monitoring, and deployment of resources in an environment. Conductor 120 may act as an integration point with third-party solutions and applications.

Conductor 120 may manage a fleet of robots 130, connecting and executing robots 130 from a centralized point. Types of robots 130 that may be managed include, but are not limited to, attended robots 132, unattended robots 134, development robots (similar to unattended robots 134, but used for development and testing purposes), and nonproduction robots (similar to attended robots 132, but used for development and testing purposes). Attended robots 132 are triggered by user events and operate alongside a human on the same computing system. Attended robots 132 may be used with conductor 120 for a centralized process deployment and logging medium. Attended robots 132 may help the human user accomplish various tasks, and may be triggered by user events. In some embodiments, processes cannot be started from conductor 120 on this type of robot and/or they cannot run under a locked screen. In certain embodiments, attended robots 132 can only be started from a robot tray or from a command prompt. Attended robots 132 should run under human supervision in some embodiments.

Unattended robots 134 run unattended in virtual environments and can automate many processes. Unattended robots 134 may be responsible for remote execution, monitoring, scheduling, and providing support for work queues. Debugging for all robot types may be run in designer 110 in some embodiments. Both attended and unattended robots may automate various systems and applications including, but not limited to, mainframes, web applications, VMs, enterprise applications (e.g., those produced by SAP®, SalesForce®, Oracle®, etc.), and computing system applications (e.g., desktop and laptop applications, mobile device applications, wearable computer applications, etc.).

Conductor 120 may have various capabilities including, but not limited to, provisioning, deployment, configuration, queueing, monitoring, logging, and/or providing interconnectivity. Provisioning may include creating and maintenance of connections between robots 130 and conductor 120 (e.g., a web application). Deployment may include assuring the correct delivery of package versions to assigned robots 130 for execution. Configuration may include maintenance and delivery of robot environments and process configurations. Queueing may include providing management of queues and queue items. Monitoring may include keeping track of robot identification data and maintaining user permissions. Logging may include storing and indexing logs to a database (e.g., an SQL database) and/or another storage mechanism (e.g., ElasticSearch®, which provides the ability to store and quickly query large datasets). Conductor 120 may provide interconnectivity by acting as the centralized point of communication for third-party solutions and/or applications.

Robots 130 are execution agents that run workflows built in designer 110. One commercial example of some embodiments of robot(s) 130 is UiPath Robots™. In some embodiments, robots 130 install the Microsoft Windows® Service Control Manager (SCM)-managed service by default. As a result, such robots 130 can open interactive Windows® sessions under the local system account, and have the rights of a Windows® service.

In some embodiments, robots 130 can be installed in a user mode. For such robots 130, this means they have the same rights as the user under which a given robot 130 has been installed. This feature may also be available for High Density (HD) robots, which ensure full utilization of each machine at its maximum potential. In some embodiments, any type of robot 130 may be configured in an HD environment.

Robots 130 in some embodiments are split into several components, each being dedicated to a particular automation task. The robot components in some embodiments include, but are not limited to, SCM-managed robot services, user mode robot services, executors, agents, and command line. SCM-managed robot services manage and monitor Windows® sessions and act as a proxy between conductor 120 and the execution hosts (i.e., the computing systems on which robots 130 are executed). These services are trusted with and manage the credentials for robots 130. A console application is launched by the SCM under the local system.

User mode robot services in some embodiments manage and monitor Windows® sessions and act as a proxy between conductor 120 and the execution hosts. User mode robot services may be trusted with and manage the credentials for robots 130. A Windows® application may automatically be launched if the SCM-managed robot service is not installed.

Executors may run given jobs under a Windows® session (i.e., they may execute workflows. Executors may be aware of per-monitor dots per inch (DPI) settings. Agents may be Windows® Presentation Foundation (WPF) applications that display the available jobs in the system tray window. Agents may be a client of the service. Agents may request to start or stop jobs and change settings. The command line is a client of the service. The command line is a console application that can request to start jobs and waits for their output.

Having components of robots 130 split as explained above helps developers, support users, and computing systems more easily run, identify, and track what each component is executing. Special behaviors may be configured per component this way, such as setting up different firewall rules for the executor and the service. The executor may always be aware of DPI settings per monitor in some embodiments. As a result, workflows may be executed at any DPI, regardless of the configuration of the computing system on which they were created. Projects from designer 110 may also be independent of browser zoom level ins some embodiments. For applications that are DPI-unaware or intentionally marked as unaware, DPI may be disabled in some embodiments.

FIG. 2 is an architectural diagram illustrating a deployed RPA system 200, according to an embodiment of the present invention. In some embodiments, RPA system 200 may be, or may be a part of, RPA system 100 of FIG. 1. It should be noted that the client side, the server side, or both, may include any desired number of computing systems without deviating from the scope of the invention. On the client side, a robot application 210 includes executors 212, an agent 214, and a designer 216. However, in some embodiments, designer 216 may not be running on computing system 210. Executors 212 are running processes. Several business projects may run simultaneously, as shown in FIG. 2. Agent 214 (e.g., a Windows® service) is the single point of contact for all executors 212 in this embodiment. All messages in this embodiment are logged into conductor 230, which processes them further via database server 240, indexer server 250, or both. As discussed above with respect to FIG. 1, executors 212 may be robot components.

In some embodiments, a robot represents an association between a machine name and a username. The robot may manage multiple executors at the same time. On computing systems that support multiple interactive sessions running simultaneously (e.g., Windows® Server 2012), multiple robots may be running at the same time, each in a separate Windows® session using a unique username. This is referred to as HD robots above.

Agent 214 is also responsible for sending the status of the robot (e.g., periodically sending a “heartbeat” message indicating that the robot is still functioning) and downloading the required version of the package to be executed. The communication between agent 214 and conductor 230 is always initiated by agent 214 in some embodiments. In the notification scenario, agent 214 may open a WebSocket channel that is later used by conductor 230 to send commands to the robot (e.g., start, stop, etc.).

On the server side, a presentation layer (web application 232, Open Data Protocol (OData) Representative State Transfer (REST) Application Programming Interface (API) endpoints 234, and notification and monitoring 236), a service layer (API implementation/business logic 238), and a persistence layer (database server 240 and indexer server 250) are included. Conductor 230 includes web application 232, OData REST API endpoints 234, notification and monitoring 236, and API implementation/business logic 238. In some embodiments, most actions that a user performs in the interface of conductor 220 (e.g., via browser 220) are performed by calling various APIs. Such actions may include, but are not limited to, starting jobs on robots, adding/removing data in queues, scheduling jobs to run unattended, etc. without deviating from the scope of the invention. Web application 232 is the visual layer of the server platform. In this embodiment, web application 232 uses Hypertext Markup Language (HTML) and JavaScript (JS). However, any desired markup languages, script languages, or any other formats may be used without deviating from the scope of the invention. The user interacts with web pages from web application 232 via browser 220 in this embodiment in order to perform various actions to control conductor 230. For instance, the user may create robot groups, assign packages to the robots, analyze logs per robot and/or per process, start and stop robots, etc.

In addition to web application 232, conductor 230 also includes service layer that exposes OData REST API endpoints 234. However, other endpoints may be included without deviating from the scope of the invention. The REST API is consumed by both web application 232 and agent 214. Agent 214 is the supervisor of one or more robots on the client computer in this embodiment.

The REST API in this embodiment covers configuration, logging, monitoring, and queueing functionality. The configuration endpoints may be used to define and configure application users, permissions, robots, assets, releases, and environments in some embodiments. Logging REST endpoints may be used to log different information, such as errors, explicit messages sent by the robots, and other environment-specific information, for instance. Deployment REST endpoints may be used by the robots to query the package version that should be executed if the start job command is used in conductor 230. Queueing REST endpoints may be responsible for queues and queue item management, such as adding data to a queue, obtaining a transaction from the queue, setting the status of a transaction, etc.

Monitoring REST endpoints may monitor web application 232 and agent 214. Notification and monitoring API 236 may be REST endpoints that are used for registering agent 214, delivering configuration settings to agent 214, and for sending/receiving notifications from the server and agent 214. Notification and monitoring API 236 may also use WebSocket communication in some embodiments.

The persistence layer includes a pair of servers in this embodiment—database server 240 (e.g., a SQL server) and indexer server 250. Database server 240 in this embodiment stores the configurations of the robots, robot groups, associated processes, users, roles, schedules, etc. This information is managed through web application 232 in some embodiments. Database server 240 may manages queues and queue items. In some embodiments, database server 240 may store messages logged by the robots (in addition to or in lieu of indexer server 250).

Indexer server 250, which is optional in some embodiments, stores and indexes the information logged by the robots. In certain embodiments, indexer server 250 may be disabled through configuration settings. In some embodiments, indexer server 250 uses ElasticSearch®, which is an open source project full-text search engine. Messages logged by robots (e.g., using activities like log message or write line) may be sent through the logging REST endpoint(s) to indexer server 250, where they are indexed for future utilization.

FIG. 3 is an architectural diagram illustrating the relationship 300 between a designer 310, activities 320, 330, and drivers 340, according to an embodiment of the present invention. Per the above, a developer uses designer 310 to develop workflows that are executed by robots. Workflows may include user-defined activities 320 and UI automation activities 330. Some embodiments are able to identify non-textual visual components in an image, which is called computer vision (CV) herein. Some CV activities pertaining to such components may include, but are not limited to, click, type, get text, hover, element exists, refresh scope, highlight, etc. Click in some embodiments identifies an element using CV, optical character recognition (OCR), fuzzy text matching, and multi-anchor, for example, and clicks it. Type may identify an element using the above and types in the element. Get text may identify the location of specific text and scan it using OCR. Hover may identify an element and hover over it. Element exists may check whether an element exists on the screen using the techniques described above. In some embodiments, there may be hundreds or even thousands of activities that can be implemented in designer 310. However, any number and/or type of activities may be available without deviating from the scope of the invention.

UI automation activities 330 are a subset of special, lower level activities that are written in lower level code (e.g., CV activities) and facilitate interactions with the screen. UI automation activities 330 facilitate these interactions via drivers 340 that allow the robot to interact with the desired software. For instance, drivers 340 may include OS drivers 342, browser drivers 344, VM drivers 346, enterprise application drivers 348, etc.

Drivers 340 may interact with the OS at a low level looking for hooks, monitoring for keys, etc. They may facilitate integration with Chrome®, IE®, Citrix®, SAP®, etc. For instance, the “click” activity performs the same role in these different applications via drivers 340.

FIG. 4 is an architectural diagram illustrating an RPA system 400, according to an embodiment of the present invention. In some embodiments, RPA system 400 may be or include RPA systems 100 and/or 200 of FIGS. 1 and/or 2. RPA system 400 includes multiple client computing systems 410 running robots. Computing systems 410 are able to communicate with a conductor computing system 420 via a web application running thereon. Conductor computing system 420, in turn, is able to communicate with a database server 430 and an optional indexer server 440.

With respect to FIGS. 1 and 3, it should be noted that while a web application is used in these embodiments, any suitable client/server software may be used without deviating from the scope of the invention. For instance, the conductor may run a server-side application that communicates with non-web-based client software applications on the client computing systems.

FIG. 5 is an architectural diagram illustrating a computing system 500 configured to create and publish one or more test cases, according to an embodiment of the present invention. In some embodiments, computing system 500 may be one or more of the computing systems depicted and/or described herein. Computing system 500 includes a bus 505 or other communication mechanism for communicating information, and processor(s) 510 coupled to bus 505 for processing information. Processor(s) 510 may be any type of general or specific purpose processor, including a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a Graphics Processing Unit (GPU), multiple instances thereof, and/or any combination thereof. Processor(s) 510 may also have multiple processing cores, and at least some of the cores may be configured to perform specific functions. Multi-parallel processing may be used in some embodiments. In certain embodiments, at least one of processor(s) 510 may be a neuromorphic circuit that includes processing elements that mimic biological neurons. In some embodiments, neuromorphic circuits may not require the typical components of a Von Neumann computing architecture.

Computing system 500 further includes a memory 515 for storing information and instructions to be executed by processor(s) 510. Memory 515 can be comprised of any combination of Random Access Memory (RAM), Read Only Memory (ROM), flash memory, cache, static storage such as a magnetic or optical disk, or any other types of non-transitory computer-readable media or combinations thereof. Non-transitory computer-readable media may be any available media that can be accessed by processor(s) 510 and may include volatile media, non-volatile media, or both. The media may also be removable, non-removable, or both.

Additionally, computing system 500 includes a communication device 520, such as a transceiver, to provide access to a communications network via a wireless and/or wired connection. In some embodiments, communication device 520 may be configured to use Frequency Division Multiple Access (FDMA), Single Carrier FDMA (SC-FDMA), Time Division Multiple Access (TDMA), Code Division Multiple Access (CDMA), Orthogonal Frequency Division Multiplexing (OFDM), Orthogonal Frequency Division Multiple Access (OFDMA), Global System for Mobile (GSM) communications, General Packet Radio Service (GPRS), Universal Mobile Telecommunications System (UMTS), cdma2000, Wideband CDMA (W-CDMA), High-Speed Downlink Packet Access (HSDPA), High-Speed Uplink Packet Access (HSUPA), High-Speed Packet Access (HSPA), Long Term Evolution (LTE), LTE Advanced (LTE-A), 802.11x, Wi-Fi, Zigbee, Ultra-WideBand (UWB), 802.16x, 802.15, Home Node-B (HnB), Bluetooth, Radio Frequency Identification (RFID), Infrared Data Association (IrDA), Near-Field Communications (NFC), fifth generation (5G), New Radio (NR), any combination thereof, and/or any other currently existing or future-implemented communications standard and/or protocol without deviating from the scope of the invention. In some embodiments, communication device 520 may include one or more antennas that are singular, arrayed, phased, switched, beamforming, beamsteering, a combination thereof, and or any other antenna configuration without deviating from the scope of the invention.

Processor(s) 510 are further coupled via bus 505 to a display 525, such as a plasma display, a Liquid Crystal Display (LCD), a Light Emitting Diode (LED) display, a Field Emission Display (FED), an Organic Light Emitting Diode (OLED) display, a flexible OLED display, a flexible substrate display, a projection display, a 4K display, a high definition display, a Retina® display, an In-Plane Switching (IPS) display, or any other suitable display for displaying information to a user. Display 525 may be configured as a touch (haptic) display, a three dimensional (3D) touch display, a multi-input touch display, a multi-touch display, etc. using resistive, capacitive, surface-acoustic wave (SAW) capacitive, infrared, optical imaging, dispersive signal technology, acoustic pulse recognition, frustrated total internal reflection, etc. Any suitable display device and haptic I/O may be used without deviating from the scope of the invention.

A keyboard 530 and a cursor control device 535, such as a computer mouse, a touchpad, etc., are further coupled to bus 505 to enable a user to interface with computing system 500. However, in certain embodiments, a physical keyboard and mouse may not be present, and the user may interact with the device solely through display 525 and/or a touchpad (not shown). Any type and combination of input devices may be used as a matter of design choice. In certain embodiments, no physical input device and/or display is present. For instance, the user may interact with computing system 500 remotely via another computing system in communication therewith, or computing system 500 may operate autonomously.

Memory 515 stores software modules that provide functionality when executed by processor(s) 510. The modules include an operating system 540 for computing system 500. The modules further include a test case module 545 that is configured to perform all, or part of the processes described herein or derivatives thereof. Computing system 500 may include one or more additional functional modules 550 that include additional functionality.

One skilled in the art will appreciate that a “system” could be embodied as a server, an embedded computing system, a personal computer, a console, a personal digital assistant (PDA), a cell phone, a tablet computing device, a quantum computing system, or any other suitable computing device, or combination of devices without deviating from the scope of the invention. Presenting the above-described functions as being performed by a “system” is not intended to limit the scope of the present invention in any way, but is intended to provide one example of the many embodiments of the present invention. Indeed, methods, systems, and apparatuses disclosed herein may be implemented in localized and distributed forms consistent with computing technology, including cloud computing systems.

It should be noted that some of the system features described in this specification have been presented as modules, in order to more particularly emphasize their implementation independence. For example, a module may be implemented as a hardware circuit comprising custom very large scale integration (VLSI) circuits or gate arrays, off-the-shelf semiconductors such as logic chips, transistors, or other discrete components. A module may also be implemented in programmable hardware devices such as field programmable gate arrays, programmable array logic, programmable logic devices, graphics processing units, or the like.

A module may also be at least partially implemented in software for execution by various types of processors. An identified unit of executable code may, for instance, include one or more physical or logical blocks of computer instructions that may, for instance, be organized as an object, procedure, or function. Nevertheless, the executables of an identified module need not be physically located together, but may include disparate instructions stored in different locations that, when joined logically together, comprise the module and achieve the stated purpose for the module. Further, modules may be stored on a computer-readable medium, which may be, for instance, a hard disk drive, flash device, RAM, tape, and/or any other such non-transitory computer-readable medium used to store data without deviating from the scope of the invention.

Indeed, a module of executable code could be a single instruction, or many instructions, and may even be distributed over several different code segments, among different programs, and across several memory devices. Similarly, operational data may be identified and illustrated herein within modules, and may be embodied in any suitable form and organized within any suitable type of data structure. The operational data may be collected as a single data set, or may be distributed over different locations including over different storage devices, and may exist, at least partially, merely as electronic signals on a system or network.

Test Case Creation

FIG. 6 is a flow diagram illustrating a process 600 for creating a test case, according to an embodiment of the present invention. In some embodiments, process 600 begins at 602 with opening an existing workflow with Studio™. As noted above, the existing workflow may be a workflow in production or under development. At 604, the existing workflow is selected to determine the scope of the workflow test case. Depending on the embodiment, either the entire workflow or one or more portions of the workflow are selected. See FIG. 10, which is an GUI 1000 illustrating a workflow being selected in Studio™, according to an embodiment of the present invention.

At 606, the selected test case is created. For example, the selected test case is created when the user of the computing device selects the ‘Create Test Case’ button from the context menu of a workflow. The created test case may be stored under the ‘Test Cases’ folder of the project.

In some embodiment, the test case uses a ‘given-when-then’ template or module. See FIG. 11, which is an GUI 1100 illustrating a ‘given-when-then’ template, according to an embodiment of the present invention. Under the ‘when’ module, the workflow under test is invoked, and therefore, placed as a reference. The idea is, that the test case does not hold a copy of the workflow under test, but rather directly references it. This is important, because the workflow under test may change over time. The ‘when’ module is primarily responsible for executing or invoking the workflow that is under test. See, for example, FIG. 12, which is a GUI 1200 illustrating a ‘when’ module, according to an embodiment of the present invention.

Under the ‘given’ module, the user of the computing device adds all required preconditions for the ‘when’ module to successfully execute. See FIG. 13, which is a GUI 1300 illustrating preconditions entered in the ‘given’ module, according to an embodiment of the present invention. For example, the required preconditions may include input parameters, applications, etc. The ‘given’ module may provide an execution environment, which ensures that the workflow runs successfully. This might include, for example, providing temporary files for the workflow to process (e.g., instead of real invoices), starting a certain application that is required for the workflow to run, or parameters and variables that are used within the workflow and that are expected as input for the workflow (e.g., an id or credentials). In some further embodiments, the ‘given’ module is configured to provide a possibility to mock steps of a workflow under test, ensuring that the workflow under test is executed without errors. The mocking includes simulating a series of steps within the workflow under test. See, for example, FIGS. 14 and 15, which are GUIs 1400, 1500 illustrating the mocking of the workflow under test, according to an embodiment. In some embodiments, the workflow under test is a test object for which you create test cases for, and is invoked by the ‘when’ module.

Further, under the ‘given’ module, the variables and/or parameters required for the workflow are automatically identified. In certain embodiments, the user may place any activities and/or actions in the ‘given’ module. Additionally, arguments/parameters can directly be provided in the ‘when’ module on the ‘Invoke Workflow’ activity, which references the workflow under test.

In one example, the workflow under test uses a variable Insurant.Name', which is part of a Data Driven Test Case (DDT). In some embodiments, DDTs are represented by a single test case definition, which is filled up with different data variations. Those variations may come from, for example, an Excel® file, and if such a data file is linked, arguments are created for each table column of the data source. When the test case is created, a variable with the same name is automatically created in the ‘given’ module. In another example, a default value of the original Insurant.Name' variable is given when available. Otherwise, the variable is left for the user of the computing device to complete the value.

Under the ‘then’ module, this module may hold any types of assertions, which represent an essential part of the test case. For purposes of explanation, essential part of the test case is the assertion or verification, it defines the test purpose (e.g., assert that the loan value is 500,000). This is how a test case proves that a certain requirement of the application under test is fulfilled. With the ‘then’ module, existing verification activities may be dragged into the ‘then’ section of the module by the user of the computing device. In one example, within the ‘when’ module, the user of the computing device may invoke a workflow that fills out an insurance application. See FIG. 16, which is a GUI 1600 illustrating a ‘then’ module, according to an embodiment of the present invention. Within the ‘then’ module, the user of the computing device may drag a ‘Verify UiElement’ activity to assert the created insurance number. See FIGS. 17 and 18, which are GUIs 1700 and 1800 illustrating an executed workflow, according to an embodiment of the present invention.

Test Case Publication

A Studio™ project may hold 1-n workflows, 1-n workflow test cases, and 1-n application test cases. When publishing, ‘Test Cases’ section of Orchestrator™ may contain a project, application test cases, and/or workflow test cases. Workflow test cases may additionally contain a reference to the original workflow that it was created for. See, for example, FIG. 19, which is a GUI 1900 illustrating test cases section having a column for ‘Linked Process’, according to an embodiment of the present invention.

FIG. 7 is a flow diagram illustrating a process 700 for publishing a test case, according to an embodiment of the present invention. In some embodiments, with Studio®, users can publish either their workflows, or their test cases. Once published, users can take the one or more test cases and group them together to test sets for execution. Process 700 may begin at 702 with creating one or more test cases in Studio®, and at 704, the one or more test cases are set to be publishable. See, for example, FIG. 32, which is a GUI 3200 illustrating a menu option to set the one or more test cases to be publishable, according to an embodiment of the present invention. At 706, the one or more test cases are triggered for publishing. See, for example, FIG. 33, which is a GUI 3300 illustrating an application for publishing in Studio®, according to an embodiment of the present invention.

At 708, a process is created for the test case package using a certain environment. See, for example, FIG. 34, which is a GUI 3400 illustrating a deployment process, according to an embodiment of the present invention. At 710, the one or more test cases appear in the ‘Test Cases’ section of Studio®. See, for example, FIG. 35, which is a GUI 3500 illustrating the created test cases in the ‘Test Case’ section, according to an embodiment of the present invention.

Workflow Test Case Execution

Executing workflow test cases is not that different from executing application test cases. For example, FIG. 8 is a flow diagram illustrating a process 800 for executing a test case, according to an embodiment of the present invention. In some embodiments, process 800 may begin at 802 with creating a test set, and at 804, assigning one or more test cases for one or more workflows, or one or more parts of the workflow, to the test set. At 806, the test set is executed.

It should be appreciated that the execution result of workflow test cases may have a similar structure as common application test results, but additionally may have a reference to the process under test. FIG. 20 is a GUI 2000 illustrating test results from executed workflow test cases, according to an embodiment of the present invention.

In case of a failed workflow test case, the corresponding processes within the Process' section of Orchestrator™ receives a warning triangle and tooltip. FIG. 21 is a GUI 2100 illustrating the ‘Process’ section of Orchestrator™, according to an embodiment of the present invention. In an embodiment, warning triangle and tooltip 2102 provides an indication that a particular process is affected by the failed workflow test case and may require adaptions to run successfully during production.

When considering that one or more users may continuously run one or more workflow test cases for the latest version of a workflow within a dedicated test environment, the actual process in production uses the previous version and a different environment. For example, during development of a RPA, there is a first version and then a second version. For this second version, test cases are executed when there is a change in the workflow. In another example, when the second version is under production, a set of workflow test cases are also executed during production. For instance, the test cases are executed once per day prior to running the workflow in production. With this, workflows under test can be broken and fixed prior to the workflow entering the production stage. For purposes of explanation, the term ‘environment’ refers to the system, i.e., the programming, the databases, etc. In other words, there are many environments, starting with development environment, and pre-production environment, production environment, to name a few.

For this reason, it may be beneficial to warn or notify users about potential issues within this process. Therefore, tooltip or notification message 2102 may provide the necessary context. For example, tooltip or notification message 2102 may include the following message: “Several Test Cases assigned to this process failed for version X.X.X on environment Y.” A context menu in some embodiments allows marking the warning as ‘received’ which basically removes the warning.

In certain embodiments, a failed workflow test case causes the developer to analyze the workflow and/or test case and debug the workflow and/or testcase in Studio™. Therefore, an additional context menu entry, such as that shown in FIG. 22, allows for directly opening up of the corresponding Studio™ project. FIG. 22 is a GUI 2200 illustrating an additional context menu entry 2202 to open the failed workflow test case in Studio™, according to an embodiment of the present invention. FIG. 23 is a GUI 2300 illustrating affected workflow 2302 and a test case in Studio™, according to an embodiment of the present invention.

Create Data-Driven Workflow Test Cases

In some embodiments, testing different combinations of input data requires a possibility to connect an external data source with a test case. In one example, let's assume the data source is a table within an Excel® sheet. See, for example, FIG. 24, which is a GUI 2400 illustrating a table within Excel®, according to an embodiment of the present invention.

FIG. 9 is a flow diagram illustrating a process 900 for creating a data-driven workflow test case, according to an embodiment of the present invention. In some embodiments, process 900 may begin at 902 with selecting the workflow, or one or more parts of the workflow, in Studio™. This way, the data in the data source, in this example being in the form of an Excel® sheet is leveraged. FIG. 25 is a GUI 2500 illustrating a workflow 2502 that is to be selected, according to an embodiment of the present invention. At 904, from the ‘Workflow Testing’ section, the ‘Create Data-Driven Test Case’ is selected and the data source is selected. FIG. 26 is a GUI 2600 illustrating a ‘Data-Driven Test Case’ menu 2602 allowing a user to select the data source, according to an embodiment of the present invention.

At 906, under a ‘Select Table’ menu, one or more tables are selected. Once the table(s) are selected, the fields are selected at 908. FIG. 27 is a GUI 2700 illustrating a menu option 2702 allowing fields to be selected, according to an embodiment of the present invention. Specifically, GUI 2700 shows a menu option 2702 that allows a user to select one or more fields from the data source in the Excel® sheet. It is from these fields the data is extracted. At 910, since the data source is an Excel® sheet, Studio™ automatically matches the columns with the variable names used.

At 912, for those variables that cannot be matched with a certain column, the user manually selects from available columns within the selected sheet. FIG. 28 is a GUI 2800 illustrating a menu option 2802 for allowing a user to select one or more available columns within the selected Excel® sheet, according to an embodiment of the present invention.

At 914, the data source is imported by selected on the ‘Import Data Set’ checkbox in Studio™. It should be noted that depending on the embodiment, the data source is either referenced (by path) or imported as part of the project (e.g., by clicking on the ‘Import Data Set’ checkbox in the menu option). FIG. 29 is a GUI 2900 illustrating a menu option 2902 showing an option to select ‘Import Data Set’, according to an embodiment of the present invention. In some embodiments, the data set is part of the project itself and the initial source (file) does not have to be available during test execution.

At 916, after variable matching is complete, the first test case is created and the variables within the ‘Arguments’ section are set with references to the data source (external or internal). FIG. 30 is a GUI 3000 illustrating a first test case 3002 created from the data set, according to an embodiment of the present invention.

FIG. 31 is a GUI 3100 illustrating a test case with multiple test data variations, according to an embodiment of the present invention. In some embodiments, a new tab called ‘Data Sets’ may be created showing a table with the imported test data. This table has mainly two purposes. First, the table indicates the single test case is connected to multiple test data variations. Second, the table executes one or more of the variations (e.g., by selecting one or more variations and clicking ‘Run’) for debugging purposes locally. For example, when publishing to Orchestrator™, the entire data set is published and is executed.

Some embodiments of the present invention also pertain to the creation of an algorithm that generates an automated UiPath® test case based on an underlying automated UiPath® workflow. The generated test case is in the form of a test script, represented via XAML files, and are executable via UiPath StudioPro™. The generation of 1-n test cases are expected, where 1 test case traverses a specific path through the workflow. The amount of test cases generated might differ depending on the complexity of the underlying workflow, but in total, the number of test cases should lead to the highest possible transition coverage (usually this should be +80% transition and activity coverage—assuming that the workflow under test does not include unreachable code segments).

Concolic Execution

FIG. 36 is a flow diagram illustrating a process 3600 for executing a workflow, according to an embodiment of the present invention. Process 3600 may begin with either symbolic execution 3602 or fuzzing 3604. With symbolic execution, the workflow does not have to be executed to generate a test case. The downside, however, is that 100 percent test coverage for complex workflows is not realized or achieved.

Fuzzing, on the other hand, requires the workflow to be executed with random inputs (probably several hundred times) with the upside that the test coverage is very high. Typically, when symbolic execution is performed, and if the result is sufficient, no further execution is required. Otherwise, fuzzing may be executed, which will run unattended in the background for hours, but generate accurate results.

It should be appreciated that the expected coverage rate of symbolic execution is 70 percent with an execution time of several minutes per medium to complex workflows. The coverage rate for fuzzing, however, is 90 percent or more with an expected execution time of several hours per medium to complex workflows.

FIG. 37 is a flow diagram illustrating a process 3700 for performing symbolic execution, according to an embodiment of the present invention. In some embodiments, process 3700 begins at 3702 with analyzing an automated workflow to determine what inputs cause each branch of the workflow to execute. In this step, each action and decision, which is part of the implementation, is analyzed. It should be noted, however, that the workflow is not executed. At 3704, evaluate which input causes certain outputs within the workflow.

In other words, with symbolic execution, automated workflows are analyzed to determine what inputs cause each branch of the workflow to execute. An interpreter may follow the program assuming the symbolic values for inputs rather than obtaining actual inputs as normal execution of the program would. It, thus, arrives at expressions in terms of those symbols for expressions and variables in the program, and constraints in terms of those symbols for the possible outcomes of each conditional branch. Constraints may be defined as expressions that, based on an input, leads to a certain decision. Finally, the possible inputs that trigger a branch can be determined by solving the constraints.

In short, symbolic execution works well when the number of variables is small, or when the number of paths is not high, or when there are not too many dependencies when computing various variables.

FIG. 38 is a flow diagram illustrating a process 3800 for performing fuzzing, according to an embodiment of the present invention. In this embodiment, process 3800 begins at 3802 with a robot providing (or generating) randomized typed data inputs. The typed data input may be a string, integer, or a complex type. In one example, let's say that the required input is an integer and the fuzzed input is 5. In this case, the generated random value (i.e., the fuzzed input) must meet the input criteria. For example, UiPath Studio™ uses .net as its underlying development framework—all .net object types therefore can be used as input arguments such as primitive types (e.g., Boolean, char, int, decimal, etc.) and complex types (e.g., object of type user with properties such as name, birth date, address, etc.).

At 3804, the workflow is executed as a black box with the fuzzed input, and the output of the workflow is measured. In some embodiments, measuring is performed by analyzing the output of the workflow. The output of the workflow can be a real output value, such as a string or integer, or it may be the fact that the workflow successfully complete (e.g., successfully processed an invoice workflow).

Unlike symbolic execution, which is a type of white-box testing, with fuzzying execution, the inner implementation of the workflow is not known. Instead, only the arguments that should be inputted into the workflow are known, as well as what arguments are expected as outputs from the workflow are known. The success criteria for fuzzying in one example therefore is, ‘Did we reach a defined end state of the workflow and did the output argument of this end state meet the expression defined by the workflow?’ In this example, for a workflow directed to processing a loan quote, an input such as, applicant's details, are provided to the workflow, and the expected result could be either (1) quote is successfully created or quote is declined due to for example insufficient income or age.

At 3806, process 3800 examines the workflow (e.g., based on the output of the workflow) to determine if one or more new paths are discovered through the workflow. If one or more new paths are discovered, the fuzzed input is successful and a new test case is created for each of the one or more discovered new paths at 3808. Otherwise, if a new path is not discovered, then process 3800 returns to 3802. This process may continue until one or more new paths are created.

EXAMPLES OF NEW PATHS BEING DISCOVERED: In one example, the workflow under test solves the task of processing loan requests that came in by ordinary mail. The workflow therefore monitors a mailbox and whenever a new request comes in, reads the details from the mail and inputs the data into a loan request web mask.

Depending on the data, the outcome may vary:

-   -   (1) the applicant is younger than 18 years=>the application will         be denied     -   (2) the applicant is older than 80 years=>the application will         be denied     -   (3) the applicant has a low yearly income=>the application will         be granted with a loan rate of 12%     -   (4) the applicant has a high yearly income=>the application will         be granted with a loan rate of only 3%     -   (5) the applicant did not provide all necessary data=>the         application will be sent back with the request to fill out the         rest of the data.

All those scenarios are built as different paths within the workflow. The challenge for the algorithm is not to find data that would trigger each of those different paths. Instead, the challenge is to discover all paths that are available within a workflow. For example, if the algorithm now provides data that discovers e.g. path (1), a new Test Case is created. If the algorithm within another iteration provides different data that still finds or discovers path (1), a new Test Case will not be created, since path(1) is already covered.

At 3810, process 3800 determines if a desired path coverage has been reached, i.e., determine whether most of the paths within the workflow have been discovered. It should be appreciated that before starting the automatic test case creation, the user has to define a desired path coverage for the workflow. This is represented by a percentage value (e.g., 80%, 90%, etc.) of activities within the workflow invoked during the execution. The algorithm associated with process 3800 measures the coverage reached after each test case creation—when the desired percantage is reached, the fuzzying process will cease. If desired path coverage is not reached, process 300 returns to 3802. This way, process 3800 is repeated until a predefined coverage threshold is reached, allowing for multiple test cases to be created.

In short, with the fuzzing process, real execution of the workflow is performed by providing randomized typed data inputs and measuring the actual output against the expected output. Based on the result, the data is modified, and the process is repeated until a certain threshold is reached. may require the workflow to be executed multiple times, which requires some sort of sandbox or mocking.

Unlike symbolic execution, where the workflow graph is analyzed, in fuzzing, the workflow is executed to measure the expected output. Executing the workflow requires an environment in place that allows the workflow to be executed. For example, with processing loan quotes, the workflow may require a browser with access to the web form to input the data.

While for complex workflows could take up several hours until the expected threshold is reached, process 3800 has the potential to generate high code coverage. With this embodiment, a black box environment is created, i.e., the actual inner implementation of the workflow is unknown. The only known factors are the input parameters and the expected output parameters (i.e., whether the workflow is successful). In other words, the inner workflow, including the steps or branches, are not known.

The process steps performed in FIGS. 6-9 and 36-38 may be performed by a computer program, encoding instructions for the processor(s) to perform at least part of the process(es) described in FIGS. 6-9 and 36-38, in accordance with embodiments of the present invention. The computer program may be embodied on a non-transitory computer-readable medium. The computer-readable medium may be, but is not limited to, a hard disk drive, a flash device, RAM, a tape, and/or any other such medium or combination of media used to store data. The computer program may include encoded instructions for controlling processor(s) of a computing system (e.g., processor(s) 510 of computing system 500 of FIG. 5) to implement all or part of the process steps described in FIGS. 6-9 and 36-38, which may also be stored on the computer-readable medium.

The computer program can be implemented in hardware, software, or a hybrid implementation. The computer program can be composed of modules that are in operative communication with one another, and which are designed to pass information or instructions to display. The computer program can be configured to operate on a general purpose computer, an ASIC, or any other suitable device.

In an embodiment, a computer-implemented method for performing fuzzing on a workflow using a RPA robot includes providing, by the RPA robot, a randomized typed data input in a workflow, and executing, by the RPA robot, the workflow as a black box with the randomized typed data input. The method also includes creating, by the RPA robot, a test case when a new path is discovered based on an output of the workflow, and terminating, by the RPA robot, the method when a desired path coverage has been reached.

In the embodiment, the randomized typed data input comprising a string, integer, or a complex type, wherein the complex type comprising an object of type user with one or more properties.

In the embodiment, the method includes analyzing, by the RPA robot, the output of the workflow. The output comprises a string or integer, or a notification that workflow is successfully processed.

In the embodiment, the method includes examining, by the RPA robot, the output of the workflow to determine if the new path is discovered, and providing, by the RPA robot, another randomized data input to be executed within the workflow, when the new path is not discovered.

In the embodiment, the new path is an output of the workflow based on the randomized data input.

In the embodiment, the method includes determining, by the RPA robot, that a desired path coverage for one or more new paths is reached when the new test case for new path is created.

In the embodiment, the method includes continuously repeating, by the RPA robot, the method for performing fuzzing until the desired path coverage is reached in order to create a plurality of test cases for the workflow.

In another embodiment, a non-transitory computer-readable medium storing a computer program comprises a RPA robot to perform fuzzing on a workflow. The computer program is configured to cause at least one processor to perform providing a randomized typed data input in a workflow, and executing the workflow as a black box with the randomized typed data input. The computer program is further configured to cause at least one processor to perform creating a test case when a new path is discovered based on an output of the workflow, and terminating the method when a desired path coverage has been reached.

In yet another embodiment, a system using a robotic process automation (RPA) robot for fuzzing a workflow includes memory comprises computer programmable instructions. The computer programmable instructions comprise the RPA robot. The system also includes at least one processor. The computer programmable instructions are configured to cause at least one processor to perform providing a randomized typed data input in a workflow, and executing the workflow as a black box with the randomized typed data input. The computer programmable instructions are further configured to cause at least one processor to perform creating a test case when a new path is discovered based on an output of the workflow, and terminating the method when a desired path coverage has been reached.

It will be readily understood that the components of various embodiments of the present invention, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the detailed description of the embodiments of the present invention, as represented in the attached figures, is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention.

The features, structures, or characteristics of the invention described throughout this specification may be combined in any suitable manner in one or more embodiments. For example, reference throughout this specification to “certain embodiments,” “some embodiments,” or similar language means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, appearances of the phrases “in certain embodiments,” “in some embodiment,” “in other embodiments,” or similar language throughout this specification do not necessarily all refer to the same group of embodiments and the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

It should be noted that reference throughout this specification to features, advantages, or similar language does not imply that all of the features and advantages that may be realized with the present invention should be or are in any single embodiment of the invention. Rather, language referring to the features and advantages is understood to mean that a specific feature, advantage, or characteristic described in connection with an embodiment is included in at least one embodiment of the present invention. Thus, discussion of the features and advantages, and similar language, throughout this specification may, but do not necessarily, refer to the same embodiment.

Furthermore, the described features, advantages, and characteristics of the invention may be combined in any suitable manner in one or more embodiments. One skilled in the relevant art will recognize that the invention can be practiced without one or more of the specific features or advantages of a particular embodiment. In other instances, additional features and advantages may be recognized in certain embodiments that may not be present in all embodiments of the invention.

One having ordinary skill in the art will readily understand that the invention as discussed above may be practiced with steps in a different order, and/or with hardware elements in configurations which are different than those which are disclosed. Therefore, although the invention has been described based upon these preferred embodiments, it would be apparent to those of skill in the art that certain modifications, variations, and alternative constructions would be apparent, while remaining within the spirit and scope of the invention. In order to determine the metes and bounds of the invention, therefore, reference should be made to the appended claims. 

1. A computer-implemented method for performing fuzzing on a workflow using a robotic process automation (RPA) robot, comprising: providing, by the RPA robot, a randomized typed data input in a workflow; executing, by the RPA robot, the workflow as a black box with the randomized typed data input; creating, by the RPA robot, a test case when a new path is discovered based on an output of the workflow; and terminating, by the RPA robot, the method when a desired path coverage has been reached.
 2. The computer-implemented method of claim 1, wherein the randomized typed data input comprising a string, integer, or a complex type, the complex type comprising an object of type user with one or more properties.
 3. The computer-implemented method of claim 1, further comprising: analyzing, by the RPA robot, the output of the workflow, wherein the output comprises a string or integer, or a notification that workflow is successfully processed.
 4. The computer-implemented method of claim 1, further comprising: examining, by the RPA robot, the output of the workflow to determine if the new path is discovered; and providing, by the RPA robot, another randomized data input to be executed within the workflow, when the new path is not discovered.
 5. The computer-implemented method of claim of claim 1, wherein the new path is an output of the workflow based on the randomized data input.
 6. The computer-implemented method of claim 1, further comprising: determining, by the RPA robot, that a desired path coverage for one or more new paths is reached when the new test case for new path is created.
 7. The computer-implemented method of claim 6, further comprising: continuously repeating, by the RPA robot, the method for performing fuzzing until the desired path coverage is reached in order to create a plurality of test cases for the workflow.
 8. A non-transitory computer-readable medium storing a computer program comprising a robotic processing automation (RPA) robot to perform fuzzing on a workflow, the computer program configured to cause at least one processor to perform: providing a randomized typed data input in a workflow; executing the workflow as a black box with the randomized typed data input; creating a test case when a new path is discovered based on an output of the workflow; and terminating the method when a desired path coverage has been reached.
 9. The non-transitory computer-readable medium of claim 8, wherein the randomized typed data input comprising a string, integer, or a complex type, the complex type comprising an object of type user with one or more properties.
 10. The non-transitory computer-readable medium of claim 8, wherein the computer program is further configured to cause the at least one processor to perform: analyzing the output of the workflow, wherein the output comprises a string or integer, or a notification that workflow is successfully processed.
 11. The non-transitory computer-readable medium of claim 8, wherein the computer program is further configured to cause the at least one processor to perform: examining the output of the workflow to determine if the new path is discovered; and providing another randomized data input to be executed within the workflow, when the new path is not discovered.
 12. The non-transitory computer-readable medium of claim 8, wherein the new path is an output of the workflow based on the randomized data input.
 13. The non-transitory computer-readable medium of claim 8, wherein the computer program is further configured to cause the at least one processor to perform: determining that a desired path coverage for one or more new paths is reached when the new test case for new path is created.
 14. The non-transitory computer-readable medium of claim 13, wherein the computer program is further configured to cause the at least one processor to perform: continuously repeating the method for performing fuzzing until the desired path coverage is reached in order to create a plurality of test cases for the workflow.
 15. A system using a robotic process automation (RPA) robot for fuzzing a workflow, comprising: memory comprising computer programmable instructions, the computer programmable instructions comprising the RPA robot; and at least one processor, wherein the computer programmable instructions are configured to cause at least one processor to perform: providing a randomized typed data input in a workflow; executing the workflow as a black box with the randomized typed data input; creating a test case when a new path is discovered based on an output of the workflow; and terminating the method when a desired path coverage has been reached.
 16. The system of claim 15, wherein the randomized typed data input comprising a string, integer, or a complex type, the complex type comprising an object of type user with one or more properties.
 17. The system of claim 15, the computer programmable instructions are further configured to cause at least one processor to perform: analyzing the output of the workflow, wherein the output comprises a string or integer, or a notification that workflow is successfully processed.
 18. The system of claim 15, the computer programmable instructions are further configured to cause at least one processor to perform: examining the output of the workflow to determine if the new path is discovered; and providing another randomized data input to be executed within the workflow, when the new path is not discovered.
 19. The system of claim 15, wherein the new path is an output of the workflow based on the randomized data input.
 20. The system of claim 15, the computer programmable instructions are further configured to cause at least one processor to perform: determining that a desired path coverage for one or more new paths is reached when the new test case for new path is created; and continuously repeating the method for performing fuzzing until the desired path coverage is reached in order to create a plurality of test cases for the workflow. 